Incumplimiento de pago de tarjeta de crédito (Limpio)

Dataset statistics

Number of variables	84
Number of observations	30000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	5.4 MiB
Average record size in memory	189.0 B

Variable types

Numeric	15
Categorical	69

Warnings

`education_5` has constant value "0"	Constant
`education_6` has constant value "0"	Constant
`bill_amt1` is highly correlated with `bill_amt2` and 4 other fields	High correlation
`bill_amt2` is highly correlated with `bill_amt1` and 4 other fields	High correlation
`bill_amt3` is highly correlated with `bill_amt1` and 4 other fields	High correlation
`bill_amt4` is highly correlated with `bill_amt1` and 4 other fields	High correlation
`bill_amt5` is highly correlated with `bill_amt1` and 4 other fields	High correlation
`bill_amt6` is highly correlated with `bill_amt1` and 4 other fields	High correlation
`pay_1_-1` is highly correlated with `pay_2_-1` and 2 other fields	High correlation
`pay_1_0` is highly correlated with `pay_2_0` and 3 other fields	High correlation
`pay_1_6` is highly correlated with `pay_2_5`	High correlation
`pay_1_7` is highly correlated with `pay_2_6` and 1 other fields	High correlation
`pay_1_8` is highly correlated with `pay_2_7` and 2 other fields	High correlation
`pay_2_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_2_0` is highly correlated with `pay_1_0` and 5 other fields	High correlation
`pay_2_2` is highly correlated with `pay_3_2`	High correlation
`pay_2_4` is highly correlated with `pay_3_3`	High correlation
`pay_2_5` is highly correlated with `pay_1_6` and 1 other fields	High correlation
`pay_2_6` is highly correlated with `pay_1_7` and 1 other fields	High correlation
`pay_2_7` is highly correlated with `pay_1_8` and 2 other fields	High correlation
`pay_3_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_3_0` is highly correlated with `pay_1_0` and 5 other fields	High correlation
`pay_3_1` is highly correlated with `pay_4_1`	High correlation
`pay_3_2` is highly correlated with `pay_2_2` and 1 other fields	High correlation
`pay_3_3` is highly correlated with `pay_2_4`	High correlation
`pay_3_4` is highly correlated with `pay_2_5`	High correlation
`pay_3_5` is highly correlated with `pay_1_7` and 1 other fields	High correlation
`pay_3_6` is highly correlated with `pay_1_8` and 2 other fields	High correlation
`pay_3_7` is highly correlated with `pay_4_7` and 2 other fields	High correlation
`pay_3_8` is highly correlated with `pay_5_8`	High correlation
`pay_4_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_4_0` is highly correlated with `pay_1_0` and 5 other fields	High correlation
`pay_4_1` is highly correlated with `pay_3_1`	High correlation
`pay_4_2` is highly correlated with `pay_3_2` and 1 other fields	High correlation
`pay_4_5` is highly correlated with `pay_1_8` and 3 other fields	High correlation
`pay_4_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_4_8` is highly correlated with `pay_5_8`	High correlation
`pay_5_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`pay_5_0` is highly correlated with `pay_1_0` and 5 other fields	High correlation
`pay_5_2` is highly correlated with `pay_4_2` and 1 other fields	High correlation
`pay_5_4` is highly correlated with `pay_4_5`	High correlation
`pay_5_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_5_8` is highly correlated with `pay_3_8` and 2 other fields	High correlation
`pay_6_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`pay_6_0` is highly correlated with `pay_2_0` and 4 other fields	High correlation
`pay_6_2` is highly correlated with `pay_5_2`	High correlation
`pay_6_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_6_8` is highly correlated with `pay_5_8`	High correlation
`education_1` is highly correlated with `education_2`	High correlation
`education_2` is highly correlated with `education_1`	High correlation
`marriage_1` is highly correlated with `marriage_2`	High correlation
`marriage_2` is highly correlated with `marriage_1`	High correlation
`bill_amt1` is highly correlated with `bill_amt2` and 11 other fields	High correlation
`bill_amt2` is highly correlated with `bill_amt1` and 11 other fields	High correlation
`bill_amt3` is highly correlated with `bill_amt1` and 11 other fields	High correlation
`bill_amt4` is highly correlated with `bill_amt1` and 13 other fields	High correlation
`bill_amt5` is highly correlated with `bill_amt1` and 12 other fields	High correlation
`bill_amt6` is highly correlated with `bill_amt1` and 9 other fields	High correlation
`pay_amt1` is highly correlated with `bill_amt1` and 5 other fields	High correlation
`pay_amt2` is highly correlated with `bill_amt3` and 5 other fields	High correlation
`pay_amt3` is highly correlated with `bill_amt4` and 7 other fields	High correlation
`pay_amt4` is highly correlated with `bill_amt4` and 6 other fields	High correlation
`pay_amt5` is highly correlated with `bill_amt4` and 5 other fields	High correlation
`pay_amt6` is highly correlated with `bill_amt5` and 4 other fields	High correlation
`pay_1_-1` is highly correlated with `pay_2_-1` and 2 other fields	High correlation
`pay_1_0` is highly correlated with `bill_amt1` and 5 other fields	High correlation
`pay_1_6` is highly correlated with `pay_2_5`	High correlation
`pay_1_7` is highly correlated with `pay_2_6` and 1 other fields	High correlation
`pay_1_8` is highly correlated with `pay_2_7` and 2 other fields	High correlation
`pay_2_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_2_0` is highly correlated with `bill_amt1` and 8 other fields	High correlation
`pay_2_2` is highly correlated with `pay_3_2`	High correlation
`pay_2_4` is highly correlated with `pay_3_3`	High correlation
`pay_2_5` is highly correlated with `pay_1_6` and 1 other fields	High correlation
`pay_2_6` is highly correlated with `pay_1_7` and 1 other fields	High correlation
`pay_2_7` is highly correlated with `pay_1_8` and 2 other fields	High correlation
`pay_3_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_3_0` is highly correlated with `bill_amt1` and 9 other fields	High correlation
`pay_3_1` is highly correlated with `pay_4_1`	High correlation
`pay_3_2` is highly correlated with `pay_2_2` and 1 other fields	High correlation
`pay_3_3` is highly correlated with `pay_2_4`	High correlation
`pay_3_4` is highly correlated with `pay_2_5`	High correlation
`pay_3_5` is highly correlated with `pay_1_7` and 1 other fields	High correlation
`pay_3_6` is highly correlated with `pay_1_8` and 2 other fields	High correlation
`pay_3_7` is highly correlated with `pay_4_7` and 2 other fields	High correlation
`pay_3_8` is highly correlated with `pay_5_8`	High correlation
`pay_4_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_4_0` is highly correlated with `bill_amt1` and 10 other fields	High correlation
`pay_4_1` is highly correlated with `pay_3_1`	High correlation
`pay_4_2` is highly correlated with `pay_3_2` and 1 other fields	High correlation
`pay_4_5` is highly correlated with `pay_1_8` and 3 other fields	High correlation
`pay_4_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_4_8` is highly correlated with `pay_5_8`	High correlation
`pay_5_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`pay_5_0` is highly correlated with `bill_amt1` and 10 other fields	High correlation
`pay_5_2` is highly correlated with `pay_4_2` and 1 other fields	High correlation
`pay_5_4` is highly correlated with `pay_4_5`	High correlation
`pay_5_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_5_8` is highly correlated with `pay_3_8` and 2 other fields	High correlation
`pay_6_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`pay_6_0` is highly correlated with `bill_amt1` and 10 other fields	High correlation
`pay_6_2` is highly correlated with `pay_5_2`	High correlation
`pay_6_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_6_8` is highly correlated with `pay_5_8`	High correlation
`education_1` is highly correlated with `education_2`	High correlation
`education_2` is highly correlated with `education_1`	High correlation
`marriage_1` is highly correlated with `marriage_2`	High correlation
`marriage_2` is highly correlated with `marriage_1`	High correlation
`bill_amt1` is highly correlated with `bill_amt2` and 4 other fields	High correlation
`bill_amt2` is highly correlated with `bill_amt1` and 6 other fields	High correlation
`bill_amt3` is highly correlated with `bill_amt1` and 6 other fields	High correlation
`bill_amt4` is highly correlated with `bill_amt1` and 4 other fields	High correlation
`bill_amt5` is highly correlated with `bill_amt1` and 5 other fields	High correlation
`bill_amt6` is highly correlated with `bill_amt1` and 5 other fields	High correlation
`pay_amt1` is highly correlated with `bill_amt2`	High correlation
`pay_amt2` is highly correlated with `bill_amt3`	High correlation
`pay_amt4` is highly correlated with `bill_amt5`	High correlation
`pay_amt5` is highly correlated with `bill_amt6`	High correlation
`pay_1_-1` is highly correlated with `pay_2_-1` and 2 other fields	High correlation
`pay_1_0` is highly correlated with `pay_2_0` and 3 other fields	High correlation
`pay_1_6` is highly correlated with `pay_2_5`	High correlation
`pay_1_7` is highly correlated with `pay_2_6` and 1 other fields	High correlation
`pay_1_8` is highly correlated with `pay_2_7` and 2 other fields	High correlation
`pay_2_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_2_0` is highly correlated with `pay_1_0` and 5 other fields	High correlation
`pay_2_2` is highly correlated with `pay_3_2`	High correlation
`pay_2_4` is highly correlated with `pay_3_3`	High correlation
`pay_2_5` is highly correlated with `pay_1_6` and 1 other fields	High correlation
`pay_2_6` is highly correlated with `pay_1_7` and 1 other fields	High correlation
`pay_2_7` is highly correlated with `pay_1_8` and 2 other fields	High correlation
`pay_3_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_3_0` is highly correlated with `bill_amt2` and 6 other fields	High correlation
`pay_3_1` is highly correlated with `pay_4_1`	High correlation
`pay_3_2` is highly correlated with `pay_2_2` and 1 other fields	High correlation
`pay_3_3` is highly correlated with `pay_2_4`	High correlation
`pay_3_4` is highly correlated with `pay_2_5`	High correlation
`pay_3_5` is highly correlated with `pay_1_7` and 1 other fields	High correlation
`pay_3_6` is highly correlated with `pay_1_8` and 2 other fields	High correlation
`pay_3_7` is highly correlated with `pay_4_7` and 2 other fields	High correlation
`pay_3_8` is highly correlated with `pay_5_8`	High correlation
`pay_4_-1` is highly correlated with `pay_1_-1` and 5 other fields	High correlation
`pay_4_0` is highly correlated with `bill_amt3` and 6 other fields	High correlation
`pay_4_1` is highly correlated with `pay_3_1`	High correlation
`pay_4_2` is highly correlated with `pay_3_2` and 1 other fields	High correlation
`pay_4_5` is highly correlated with `pay_1_8` and 3 other fields	High correlation
`pay_4_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_4_8` is highly correlated with `pay_5_8`	High correlation
`pay_5_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`pay_5_0` is highly correlated with `pay_1_0` and 5 other fields	High correlation
`pay_5_2` is highly correlated with `pay_4_2` and 1 other fields	High correlation
`pay_5_4` is highly correlated with `pay_4_5`	High correlation
`pay_5_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_5_8` is highly correlated with `pay_3_8` and 2 other fields	High correlation
`pay_6_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`pay_6_0` is highly correlated with `pay_2_0` and 4 other fields	High correlation
`pay_6_2` is highly correlated with `pay_5_2`	High correlation
`pay_6_7` is highly correlated with `pay_3_7` and 2 other fields	High correlation
`pay_6_8` is highly correlated with `pay_5_8`	High correlation
`education_1` is highly correlated with `education_2`	High correlation
`education_2` is highly correlated with `education_1`	High correlation
`marriage_1` is highly correlated with `marriage_2`	High correlation
`marriage_2` is highly correlated with `marriage_1`	High correlation
`pay_amt4` is highly correlated with `pay_amt3` and 1 other fields	High correlation
`pay_2_-1` is highly correlated with `pay_6_-1` and 8 other fields	High correlation
`pay_5_7` is highly correlated with `pay_6_7` and 2 other fields	High correlation
`pay_4_4` is highly correlated with `pay_2_6` and 5 other fields	High correlation
`pay_4_5` is highly correlated with `pay_3_6` and 4 other fields	High correlation
`pay_amt2` is highly correlated with `pay_amt5` and 3 other fields	High correlation
`pay_5_2` is highly correlated with `pay_4_2` and 4 other fields	High correlation
`pay_4_2` is highly correlated with `pay_5_2` and 4 other fields	High correlation
`pay_6_-1` is highly correlated with `pay_2_-1` and 6 other fields	High correlation
`marriage_2` is highly correlated with `marriage_1` and 1 other fields	High correlation
`pay_3_3` is highly correlated with `pay_2_4`	High correlation
`pay_3_1` is highly correlated with `pay_4_1`	High correlation
`bill_amt2` is highly correlated with `bill_amt1` and 6 other fields	High correlation
`pay_2_0` is highly correlated with `pay_2_-1` and 10 other fields	High correlation
`pay_4_8` is highly correlated with `pay_5_8` and 1 other fields	High correlation
`pay_1_0` is highly correlated with `pay_2_-1` and 9 other fields	High correlation
`pay_2_6` is highly correlated with `pay_4_4` and 2 other fields	High correlation
`pay_1_-1` is highly correlated with `pay_2_-1` and 7 other fields	High correlation
`education_2` is highly correlated with `education_1` and 1 other fields	High correlation
`pay_3_6` is highly correlated with `pay_4_5` and 3 other fields	High correlation
`bill_amt1` is highly correlated with `bill_amt2` and 6 other fields	High correlation
`pay_6_8` is highly correlated with `pay_5_8` and 1 other fields	High correlation
`pay_5_8` is highly correlated with `pay_4_8` and 3 other fields	High correlation
`pay_1_1` is highly correlated with `pay_2_0` and 2 other fields	High correlation
`pay_4_-1` is highly correlated with `pay_2_-1` and 8 other fields	High correlation
`pay_6_5` is highly correlated with `pay_5_6`	High correlation
`pay_amt5` is highly correlated with `pay_amt2` and 1 other fields	High correlation
`marriage_1` is highly correlated with `marriage_2` and 1 other fields	High correlation
`pay_5_6` is highly correlated with `pay_6_5`	High correlation
`pay_6_3` is highly correlated with `pay_4_5` and 1 other fields	High correlation
`pay_2_8` is highly correlated with `pay_4_8` and 3 other fields	High correlation
`pay_amt3` is highly correlated with `pay_amt4` and 8 other fields	High correlation
`age` is highly correlated with `marriage_2` and 1 other fields	High correlation
`bill_amt4` is highly correlated with `bill_amt2` and 8 other fields	High correlation
`default_payment_next_month` is highly correlated with `pay_1_2`	High correlation
`education_1` is highly correlated with `education_2`	High correlation
`pay_3_4` is highly correlated with `pay_4_4` and 3 other fields	High correlation
`limit_bal` is highly correlated with `bill_amt2` and 5 other fields	High correlation
`pay_6_7` is highly correlated with `pay_5_7` and 2 other fields	High correlation
`pay_3_7` is highly correlated with `pay_5_7` and 2 other fields	High correlation
`pay_5_5` is highly correlated with `pay_6_4`	High correlation
`pay_4_7` is highly correlated with `pay_5_7` and 2 other fields	High correlation
`pay_4_1` is highly correlated with `pay_3_1` and 2 other fields	High correlation
`pay_1_4` is highly correlated with `pay_2_3`	High correlation
`pay_4_0` is highly correlated with `pay_2_-1` and 9 other fields	High correlation
`pay_1_5` is highly correlated with `pay_2_4`	High correlation
`pay_5_0` is highly correlated with `pay_5_2` and 9 other fields	High correlation
`pay_6_0` is highly correlated with `pay_6_-1` and 8 other fields	High correlation
`pay_5_-1` is highly correlated with `pay_2_-1` and 8 other fields	High correlation
`pay_3_0` is highly correlated with `pay_2_-1` and 10 other fields	High correlation
`pay_1_6` is highly correlated with `pay_3_4` and 1 other fields	High correlation
`pay_1_8` is highly correlated with `pay_4_5` and 3 other fields	High correlation
`education_3` is highly correlated with `education_2`	High correlation
`pay_2_3` is highly correlated with `pay_1_4`	High correlation
`pay_4_3` is highly correlated with `pay_3_4`	High correlation
`pay_1_7` is highly correlated with `pay_4_4` and 2 other fields	High correlation
`pay_6_2` is highly correlated with `pay_5_2` and 3 other fields	High correlation
`bill_amt6` is highly correlated with `bill_amt2` and 6 other fields	High correlation
`pay_1_2` is highly correlated with `default_payment_next_month` and 1 other fields	High correlation
`pay_2_2` is highly correlated with `pay_5_2` and 6 other fields	High correlation
`pay_2_5` is highly correlated with `pay_3_4` and 1 other fields	High correlation
`pay_6_4` is highly correlated with `pay_4_4` and 2 other fields	High correlation
`pay_2_7` is highly correlated with `pay_4_5` and 3 other fields	High correlation
`pay_5_3` is highly correlated with `pay_4_4`	High correlation
`pay_3_-1` is highly correlated with `pay_2_-1` and 8 other fields	High correlation
`pay_amt1` is highly correlated with `pay_amt4` and 2 other fields	High correlation
`pay_3_5` is highly correlated with `pay_4_4` and 2 other fields	High correlation
`bill_amt5` is highly correlated with `bill_amt2` and 6 other fields	High correlation
`pay_3_2` is highly correlated with `pay_5_2` and 4 other fields	High correlation
`pay_2_4` is highly correlated with `pay_3_3` and 1 other fields	High correlation
`bill_amt3` is highly correlated with `pay_amt2` and 6 other fields	High correlation
`pay_5_4` is highly correlated with `pay_4_5` and 5 other fields	High correlation
`pay_4_1` is highly correlated with `pay_3_1` and 2 other fields	High correlation
`pay_2_-1` is highly correlated with `pay_5_-1` and 7 other fields	High correlation
`pay_5_7` is highly correlated with `education_6` and 4 other fields	High correlation
`pay_1_4` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_4_4` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_4_0` is highly correlated with `pay_5_0` and 7 other fields	High correlation
`pay_4_5` is highly correlated with `pay_1_8` and 5 other fields	High correlation
`pay_1_5` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_5_0` is highly correlated with `pay_4_0` and 7 other fields	High correlation
`pay_4_2` is highly correlated with `pay_5_2` and 3 other fields	High correlation
`pay_5_-1` is highly correlated with `pay_2_-1` and 6 other fields	High correlation
`pay_5_2` is highly correlated with `pay_4_2` and 3 other fields	High correlation
`pay_6_0` is highly correlated with `pay_4_0` and 6 other fields	High correlation
`pay_6_-1` is highly correlated with `pay_2_-1` and 6 other fields	High correlation
`marriage_2` is highly correlated with `education_6` and 2 other fields	High correlation
`pay_3_3` is highly correlated with `education_6` and 2 other fields	High correlation
`pay_3_0` is highly correlated with `pay_4_0` and 7 other fields	High correlation
`pay_1_6` is highly correlated with `education_6` and 2 other fields	High correlation
`pay_1_8` is highly correlated with `pay_4_5` and 4 other fields	High correlation
`pay_2_0` is highly correlated with `pay_2_-1` and 7 other fields	High correlation
`pay_3_1` is highly correlated with `pay_4_1` and 2 other fields	High correlation
`education_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_2_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_4_8` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_1_0` is highly correlated with `pay_4_0` and 5 other fields	High correlation
`pay_2_6` is highly correlated with `education_6` and 3 other fields	High correlation
`pay_1_-1` is highly correlated with `pay_2_-1` and 4 other fields	High correlation
`education_2` is highly correlated with `education_6` and 2 other fields	High correlation
`pay_3_6` is highly correlated with `pay_4_5` and 4 other fields	High correlation
`education_6` is highly correlated with `pay_4_1` and 67 other fields	High correlation
`pay_4_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_6_8` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_1_7` is highly correlated with `pay_2_6` and 3 other fields	High correlation
`pay_5_8` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_1_1` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_6_2` is highly correlated with `pay_5_2` and 2 other fields	High correlation
`pay_1_2` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_5_4` is highly correlated with `pay_4_5` and 2 other fields	High correlation
`pay_4_-1` is highly correlated with `pay_2_-1` and 7 other fields	High correlation
`pay_6_5` is highly correlated with `education_6` and 1 other fields	High correlation
`education_5` is highly correlated with `pay_4_1` and 67 other fields	High correlation
`marriage_1` is highly correlated with `marriage_2` and 2 other fields	High correlation
`marriage_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_5_6` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_6_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_2_8` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_2_5` is highly correlated with `pay_1_6` and 3 other fields	High correlation
`pay_2_2` is highly correlated with `education_6` and 2 other fields	High correlation
`pay_6_4` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_4_6` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_2_7` is highly correlated with `pay_4_5` and 4 other fields	High correlation
`pay_2_1` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_5_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_3_-1` is highly correlated with `pay_2_-1` and 7 other fields	High correlation
`pay_6_6` is highly correlated with `education_6` and 1 other fields	High correlation
`education_4` is highly correlated with `education_6` and 1 other fields	High correlation
`default_payment_next_month` is highly correlated with `education_6` and 1 other fields	High correlation
`education_1` is highly correlated with `education_2` and 2 other fields	High correlation
`pay_3_5` is highly correlated with `pay_2_6` and 3 other fields	High correlation
`pay_3_4` is highly correlated with `education_6` and 2 other fields	High correlation
`pay_3_8` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_1_3` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_3_2` is highly correlated with `pay_4_2` and 3 other fields	High correlation
`pay_6_7` is highly correlated with `pay_5_7` and 4 other fields	High correlation
`pay_2_4` is highly correlated with `pay_3_3` and 2 other fields	High correlation
`pay_3_7` is highly correlated with `pay_5_7` and 4 other fields	High correlation
`female` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_5_5` is highly correlated with `education_6` and 1 other fields	High correlation
`pay_4_7` is highly correlated with `pay_5_7` and 4 other fields	High correlation
`pay_amt2` is highly skewed (γ1 = 30.45381745)	Skewed
`id` is uniformly distributed	Uniform
`id` has unique values	Unique
`bill_amt1` has 2008 (6.7%) zeros	Zeros
`bill_amt2` has 2506 (8.4%) zeros	Zeros
`bill_amt3` has 2870 (9.6%) zeros	Zeros
`bill_amt4` has 3195 (10.7%) zeros	Zeros
`bill_amt5` has 3506 (11.7%) zeros	Zeros
`bill_amt6` has 4020 (13.4%) zeros	Zeros
`pay_amt1` has 5249 (17.5%) zeros	Zeros
`pay_amt2` has 5396 (18.0%) zeros	Zeros
`pay_amt3` has 5968 (19.9%) zeros	Zeros
`pay_amt4` has 6408 (21.4%) zeros	Zeros
`pay_amt5` has 6703 (22.3%) zeros	Zeros
`pay_amt6` has 7173 (23.9%) zeros	Zeros

Reproduction

Analysis started	2021-11-08 21:51:54.525587
Analysis finished	2021-11-08 21:53:56.268744
Duration	2 minutes and 1.74 second
Software version	pandas-profiling v3.0.0
Download configuration	config.json

id
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	30000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15000.5

Minimum	1
Maximum	30000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1500.95
Q1	7500.75
median	15000.5
Q3	22500.25
95-th percentile	28500.05
Maximum	30000
Range	29999
Interquartile range (IQR)	14999.5

Descriptive statistics

Standard deviation	8660.398374
Coefficient of variation (CV)	0.5773406469
Kurtosis	-1.2
Mean	15000.5
Median Absolute Deviation (MAD)	7500
Skewness	0
Sum	450015000
Variance	75002500
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2047	1	< 0.1%
1322	1	< 0.1%
15629	1	< 0.1%
9486	1	< 0.1%
11535	1	< 0.1%
21792	1	< 0.1%
23841	1	< 0.1%
17698	1	< 0.1%
19747	1	< 0.1%
29988	1	< 0.1%
Other values (29990)	29990	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
30000	1	< 0.1%
29999	1	< 0.1%
29998	1	< 0.1%
29997	1	< 0.1%
29996	1	< 0.1%
29995	1	< 0.1%
29994	1	< 0.1%
29993	1	< 0.1%
29992	1	< 0.1%
29991	1	< 0.1%

limit_bal
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	81
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	167484.3227

Minimum	10000
Maximum	1000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	10000
5-th percentile	20000
Q1	50000
median	140000
Q3	240000
95-th percentile	430000
Maximum	1000000
Range	990000
Interquartile range (IQR)	190000

Descriptive statistics

Standard deviation	129747.6616
Coefficient of variation (CV)	0.7746854124
Kurtosis	0.5362628964
Mean	167484.3227
Median Absolute Deviation (MAD)	90000
Skewness	0.9928669605
Sum	5024529680
Variance	1.683445568 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50000	3365	11.2%
20000	1976	6.6%
30000	1610	5.4%
80000	1567	5.2%
200000	1528	5.1%
150000	1110	3.7%
100000	1048	3.5%
180000	995	3.3%
360000	881	2.9%
60000	825	2.8%
Other values (71)	15095	50.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10000	493	1.6%
16000	2	< 0.1%
20000	1976	6.6%
30000	1610	5.4%
40000	230	0.8%
50000	3365	11.2%
60000	825	2.8%
70000	731	2.4%
80000	1567	5.2%
90000	651	2.2%

Value	Count	Frequency (%)
1000000	1	< 0.1%
800000	2	< 0.1%
780000	2	< 0.1%
760000	1	< 0.1%
750000	4	< 0.1%
740000	2	< 0.1%
730000	2	< 0.1%
720000	3	< 0.1%
710000	6	< 0.1%
700000	8	< 0.1%

age
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	56
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	35.4855

Minimum	21
Maximum	79
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	21
5-th percentile	23
Q1	28
median	34
Q3	41
95-th percentile	53
Maximum	79
Range	58
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	9.217904068
Coefficient of variation (CV)	0.2597653709
Kurtosis	0.04430337824
Mean	35.4855
Median Absolute Deviation (MAD)	6
Skewness	0.7322458688
Sum	1064565
Variance	84.96975541
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
29	1605	5.3%
27	1477	4.9%
28	1409	4.7%
30	1395	4.7%
26	1256	4.2%
31	1217	4.1%
25	1186	4.0%
34	1162	3.9%
32	1158	3.9%
33	1146	3.8%
Other values (46)	16989	56.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
21	67	0.2%
22	560	1.9%
23	931	3.1%
24	1127	3.8%
25	1186	4.0%
26	1256	4.2%
27	1477	4.9%
28	1409	4.7%
29	1605	5.3%
30	1395	4.7%

Value	Count	Frequency (%)
79	1	< 0.1%
75	3	< 0.1%
74	1	< 0.1%
73	4	< 0.1%
72	3	< 0.1%
71	3	< 0.1%
70	10	< 0.1%
69	15	0.1%
68	5	< 0.1%
67	16	0.1%

bill_amt1
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	22723
Distinct (%)	75.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	51223.3309

Minimum	-165580
Maximum	964511
Zeros	2008
Zeros (%)	6.7%
Negative	590
Negative (%)	2.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	-165580
5-th percentile	0
Q1	3558.75
median	22381.5
Q3	67091
95-th percentile	201203.05
Maximum	964511
Range	1130091
Interquartile range (IQR)	63532.25

Descriptive statistics

Standard deviation	73635.86058
Coefficient of variation (CV)	1.437545339
Kurtosis	9.806289341
Mean	51223.3309
Median Absolute Deviation (MAD)	21800.5
Skewness	2.663861022
Sum	1536699927
Variance	5422239963
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2008	6.7%
390	244	0.8%
780	76	0.3%
326	72	0.2%
316	63	0.2%
2500	59	0.2%
396	49	0.2%
2400	39	0.1%
416	29	0.1%
1050	25	0.1%
Other values (22713)	27336	91.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-165580	1	< 0.1%
-154973	1	< 0.1%
-15308	1	< 0.1%
-14386	1	< 0.1%
-11545	1	< 0.1%
-10682	1	< 0.1%
-9802	1	< 0.1%
-9095	1	< 0.1%
-8187	1	< 0.1%
-7438	1	< 0.1%

Value	Count	Frequency (%)
964511	1	< 0.1%
746814	1	< 0.1%
653062	1	< 0.1%
630458	1	< 0.1%
626648	1	< 0.1%
621749	1	< 0.1%
613860	1	< 0.1%
610723	1	< 0.1%
608594	1	< 0.1%
604019	1	< 0.1%

bill_amt2
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	22346
Distinct (%)	74.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49179.07517

Minimum	-69777
Maximum	983931
Zeros	2506
Zeros (%)	8.4%
Negative	669
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-69777
5-th percentile	0
Q1	2984.75
median	21200
Q3	64006.25
95-th percentile	194792.2
Maximum	983931
Range	1053708
Interquartile range (IQR)	61021.5

Descriptive statistics

Standard deviation	71173.76878
Coefficient of variation (CV)	1.447236829
Kurtosis	10.30294592
Mean	49179.07517
Median Absolute Deviation (MAD)	20810
Skewness	2.705220853
Sum	1475372255
Variance	5065705363
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2506	8.4%
390	231	0.8%
780	75	0.2%
326	75	0.2%
316	72	0.2%
2500	51	0.2%
396	51	0.2%
2400	42	0.1%
-200	29	0.1%
416	28	0.1%
Other values (22336)	26840	89.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-69777	1	< 0.1%
-67526	1	< 0.1%
-33350	1	< 0.1%
-30000	1	< 0.1%
-26214	1	< 0.1%
-24704	1	< 0.1%
-24702	1	< 0.1%
-22960	1	< 0.1%
-18618	1	< 0.1%
-18088	1	< 0.1%

Value	Count	Frequency (%)
983931	1	< 0.1%
743970	1	< 0.1%
671563	1	< 0.1%
646770	1	< 0.1%
624475	1	< 0.1%
605943	1	< 0.1%
597793	1	< 0.1%
586825	1	< 0.1%
581775	1	< 0.1%
577681	1	< 0.1%

bill_amt3
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	22026
Distinct (%)	73.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	47013.1548

Minimum	-157264
Maximum	1664089
Zeros	2870
Zeros (%)	9.6%
Negative	655
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-157264
5-th percentile	0
Q1	2666.25
median	20088.5
Q3	60164.75
95-th percentile	187821.05
Maximum	1664089
Range	1821353
Interquartile range (IQR)	57498.5

Descriptive statistics

Standard deviation	69349.38743
Coefficient of variation (CV)	1.475106015
Kurtosis	19.78325514
Mean	47013.1548
Median Absolute Deviation (MAD)	19708.5
Skewness	3.087830046
Sum	1410394644
Variance	4809337537
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2870	9.6%
390	275	0.9%
780	74	0.2%
326	63	0.2%
316	62	0.2%
396	48	0.2%
2500	40	0.1%
2400	39	0.1%
416	29	0.1%
200	27	0.1%
Other values (22016)	26473	88.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-157264	1	< 0.1%
-61506	1	< 0.1%
-46127	1	< 0.1%
-34041	1	< 0.1%
-25443	1	< 0.1%
-24702	1	< 0.1%
-20320	1	< 0.1%
-17706	1	< 0.1%
-15910	1	< 0.1%
-15641	1	< 0.1%

Value	Count	Frequency (%)
1664089	1	< 0.1%
855086	1	< 0.1%
693131	1	< 0.1%
689643	1	< 0.1%
689627	1	< 0.1%
632041	1	< 0.1%
597415	1	< 0.1%
578971	1	< 0.1%
577957	1	< 0.1%
577015	1	< 0.1%

bill_amt4
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	21548
Distinct (%)	71.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	43262.94897

Minimum	-170000
Maximum	891586
Zeros	3195
Zeros (%)	10.7%
Negative	675
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-170000
5-th percentile	0
Q1	2326.75
median	19052
Q3	54506
95-th percentile	174333.35
Maximum	891586
Range	1061586
Interquartile range (IQR)	52179.25

Descriptive statistics

Standard deviation	64332.85613
Coefficient of variation (CV)	1.487019671
Kurtosis	11.30932483
Mean	43262.94897
Median Absolute Deviation (MAD)	18656
Skewness	2.821965291
Sum	1297888469
Variance	4138716378
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3195	10.7%
390	246	0.8%
780	101	0.3%
316	68	0.2%
326	62	0.2%
396	44	0.1%
150	39	0.1%
2400	39	0.1%
2500	34	0.1%
416	33	0.1%
Other values (21538)	26139	87.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-170000	1	< 0.1%
-81334	1	< 0.1%
-65167	1	< 0.1%
-50616	1	< 0.1%
-46627	1	< 0.1%
-34503	1	< 0.1%
-27490	1	< 0.1%
-24303	1	< 0.1%
-22108	1	< 0.1%
-20320	1	< 0.1%

Value	Count	Frequency (%)
891586	1	< 0.1%
706864	1	< 0.1%
628699	1	< 0.1%
616836	1	< 0.1%
572805	1	< 0.1%
569034	1	< 0.1%
565669	1	< 0.1%
563543	1	< 0.1%
548020	1	< 0.1%
542653	1	< 0.1%

bill_amt5
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	21010
Distinct (%)	70.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	40311.40097

Minimum	-81334
Maximum	927171
Zeros	3506
Zeros (%)	11.7%
Negative	655
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-81334
5-th percentile	0
Q1	1763
median	18104.5
Q3	50190.5
95-th percentile	165794.3
Maximum	927171
Range	1008505
Interquartile range (IQR)	48427.5

Descriptive statistics

Standard deviation	60797.15577
Coefficient of variation (CV)	1.508187617
Kurtosis	12.30588129
Mean	40311.40097
Median Absolute Deviation (MAD)	17688.5
Skewness	2.876379867
Sum	1209342029
Variance	3696294150
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3506	11.7%
390	235	0.8%
780	94	0.3%
316	79	0.3%
326	62	0.2%
150	58	0.2%
396	47	0.2%
2400	39	0.1%
2500	37	0.1%
416	36	0.1%
Other values (21000)	25807	86.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-81334	1	< 0.1%
-61372	1	< 0.1%
-53007	1	< 0.1%
-46627	1	< 0.1%
-37594	1	< 0.1%
-36156	1	< 0.1%
-30481	1	< 0.1%
-28335	1	< 0.1%
-23003	1	< 0.1%
-20753	1	< 0.1%

Value	Count	Frequency (%)
927171	1	< 0.1%
823540	1	< 0.1%
587067	1	< 0.1%
551702	1	< 0.1%
547880	1	< 0.1%
530672	1	< 0.1%
524315	1	< 0.1%
516139	1	< 0.1%
514114	1	< 0.1%
508213	1	< 0.1%

bill_amt6
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	20604
Distinct (%)	68.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38871.7604

Minimum	-339603
Maximum	961664
Zeros	4020
Zeros (%)	13.4%
Negative	688
Negative (%)	2.3%
Memory size	234.5 KiB

Quantile statistics

Minimum	-339603
5-th percentile	0
Q1	1256
median	17071
Q3	49198.25
95-th percentile	161912
Maximum	961664
Range	1301267
Interquartile range (IQR)	47942.25

Descriptive statistics

Standard deviation	59554.10754
Coefficient of variation (CV)	1.53206613
Kurtosis	12.27070529
Mean	38871.7604
Median Absolute Deviation (MAD)	16755
Skewness	2.846644576
Sum	1166152812
Variance	3546691724
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4020	13.4%
390	207	0.7%
780	86	0.3%
150	78	0.3%
316	77	0.3%
326	56	0.2%
396	45	0.1%
416	36	0.1%
-18	33	0.1%
2400	32	0.1%
Other values (20594)	25330	84.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-339603	1	< 0.1%
-209051	1	< 0.1%
-150953	1	< 0.1%
-94625	1	< 0.1%
-73895	1	< 0.1%
-57060	1	< 0.1%
-51443	1	< 0.1%
-51183	1	< 0.1%
-46627	1	< 0.1%
-45734	1	< 0.1%

Value	Count	Frequency (%)
961664	1	< 0.1%
699944	1	< 0.1%
568638	1	< 0.1%
527711	1	< 0.1%
527566	1	< 0.1%
514975	1	< 0.1%
513798	1	< 0.1%
511905	1	< 0.1%
501370	1	< 0.1%
499100	1	< 0.1%

pay_amt1
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7943
Distinct (%)	26.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5663.5805

Minimum	0
Maximum	873552
Zeros	5249
Zeros (%)	17.5%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1000
median	2100
Q3	5006
95-th percentile	18428.2
Maximum	873552
Range	873552
Interquartile range (IQR)	4006

Descriptive statistics

Standard deviation	16563.28035
Coefficient of variation (CV)	2.924524575
Kurtosis	415.2547427
Mean	5663.5805
Median Absolute Deviation (MAD)	1932
Skewness	14.66836433
Sum	169907415
Variance	274342256.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5249	17.5%
2000	1363	4.5%
3000	891	3.0%
5000	698	2.3%
1500	507	1.7%
4000	426	1.4%
10000	401	1.3%
1000	365	1.2%
2500	298	1.0%
6000	294	1.0%
Other values (7933)	19508	65.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5249	17.5%
1	9	< 0.1%
2	14	< 0.1%
3	15	0.1%
4	18	0.1%
5	12	< 0.1%
6	15	0.1%
7	9	< 0.1%
8	8	< 0.1%
9	7	< 0.1%

Value	Count	Frequency (%)
873552	1	< 0.1%
505000	1	< 0.1%
493358	1	< 0.1%
423903	1	< 0.1%
405016	1	< 0.1%
368199	1	< 0.1%
323014	1	< 0.1%
304815	1	< 0.1%
302000	1	< 0.1%
300039	1	< 0.1%

pay_amt2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	7899
Distinct (%)	26.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5921.1635

Minimum	0
Maximum	1684259
Zeros	5396
Zeros (%)	18.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	833
median	2009
Q3	5000
95-th percentile	19004.35
Maximum	1684259
Range	1684259
Interquartile range (IQR)	4167

Descriptive statistics

Standard deviation	23040.8704
Coefficient of variation (CV)	3.891274139
Kurtosis	1641.631911
Mean	5921.1635
Median Absolute Deviation (MAD)	1991
Skewness	30.45381745
Sum	177634905
Variance	530881708.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5396	18.0%
2000	1290	4.3%
3000	857	2.9%
5000	717	2.4%
1000	594	2.0%
1500	521	1.7%
4000	410	1.4%
10000	318	1.1%
6000	283	0.9%
2500	251	0.8%
Other values (7889)	19363	64.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5396	18.0%
1	15	0.1%
2	20	0.1%
3	18	0.1%
4	11	< 0.1%
5	25	0.1%
6	8	< 0.1%
7	12	< 0.1%
8	9	< 0.1%
9	6	< 0.1%

Value	Count	Frequency (%)
1684259	1	< 0.1%
1227082	1	< 0.1%
1215471	1	< 0.1%
1024516	1	< 0.1%
580464	1	< 0.1%
415552	1	< 0.1%
401003	1	< 0.1%
388126	1	< 0.1%
385228	1	< 0.1%
384986	1	< 0.1%

pay_amt3
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7518
Distinct (%)	25.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5225.6815

Minimum	0
Maximum	896040
Zeros	5968
Zeros (%)	19.9%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	390
median	1800
Q3	4505
95-th percentile	17589.4
Maximum	896040
Range	896040
Interquartile range (IQR)	4115

Descriptive statistics

Standard deviation	17606.96147
Coefficient of variation (CV)	3.36931393
Kurtosis	564.3112295
Mean	5225.6815
Median Absolute Deviation (MAD)	1795
Skewness	17.21663544
Sum	156770445
Variance	310005092.2
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5968	19.9%
2000	1285	4.3%
1000	1103	3.7%
3000	870	2.9%
5000	721	2.4%
1500	490	1.6%
4000	381	1.3%
10000	312	1.0%
1200	243	0.8%
6000	241	0.8%
Other values (7508)	18386	61.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5968	19.9%
1	13	< 0.1%
2	19	0.1%
3	14	< 0.1%
4	15	0.1%
5	18	0.1%
6	14	< 0.1%
7	18	0.1%
8	10	< 0.1%
9	12	< 0.1%

Value	Count	Frequency (%)
896040	1	< 0.1%
889043	1	< 0.1%
508229	1	< 0.1%
417588	1	< 0.1%
400972	1	< 0.1%
397092	1	< 0.1%
380478	1	< 0.1%
371718	1	< 0.1%
349395	1	< 0.1%
344261	1	< 0.1%

pay_amt4
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6937
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4826.076867

Minimum	0
Maximum	621000
Zeros	6408
Zeros (%)	21.4%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	296
median	1500
Q3	4013.25
95-th percentile	16014.95
Maximum	621000
Range	621000
Interquartile range (IQR)	3717.25

Descriptive statistics

Standard deviation	15666.15974
Coefficient of variation (CV)	3.246147995
Kurtosis	277.3337677
Mean	4826.076867
Median Absolute Deviation (MAD)	1500
Skewness	12.90498482
Sum	144782306
Variance	245428561.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6408	21.4%
1000	1394	4.6%
2000	1214	4.0%
3000	887	3.0%
5000	810	2.7%
1500	441	1.5%
4000	402	1.3%
10000	341	1.1%
2500	259	0.9%
500	258	0.9%
Other values (6927)	17586	58.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	6408	21.4%
1	22	0.1%
2	22	0.1%
3	13	< 0.1%
4	20	0.1%
5	12	< 0.1%
6	16	0.1%
7	11	< 0.1%
8	7	< 0.1%
9	9	< 0.1%

Value	Count	Frequency (%)
621000	1	< 0.1%
528897	1	< 0.1%
497000	1	< 0.1%
432130	1	< 0.1%
400046	1	< 0.1%
331788	1	< 0.1%
330982	1	< 0.1%
320008	1	< 0.1%
313094	1	< 0.1%
292962	1	< 0.1%

pay_amt5
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6897
Distinct (%)	23.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4799.387633

Minimum	0
Maximum	426529
Zeros	6703
Zeros (%)	22.3%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	252.5
median	1500
Q3	4031.5
95-th percentile	16000
Maximum	426529
Range	426529
Interquartile range (IQR)	3779

Descriptive statistics

Standard deviation	15278.30568
Coefficient of variation (CV)	3.183386475
Kurtosis	180.0639402
Mean	4799.387633
Median Absolute Deviation (MAD)	1500
Skewness	11.12741705
Sum	143981629
Variance	233426624.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6703	22.3%
1000	1340	4.5%
2000	1323	4.4%
3000	947	3.2%
5000	814	2.7%
1500	426	1.4%
4000	401	1.3%
10000	343	1.1%
500	250	0.8%
6000	247	0.8%
Other values (6887)	17206	57.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	6703	22.3%
1	21	0.1%
2	13	< 0.1%
3	13	< 0.1%
4	12	< 0.1%
5	9	< 0.1%
6	7	< 0.1%
7	9	< 0.1%
8	6	< 0.1%
9	6	< 0.1%

Value	Count	Frequency (%)
426529	1	< 0.1%
417990	1	< 0.1%
388071	1	< 0.1%
379267	1	< 0.1%
332000	1	< 0.1%
331788	1	< 0.1%
330982	1	< 0.1%
326889	1	< 0.1%
317077	1	< 0.1%
310135	1	< 0.1%

pay_amt6
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	6939
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5215.502567

Minimum	0
Maximum	528666
Zeros	7173
Zeros (%)	23.9%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	117.75
median	1500
Q3	4000
95-th percentile	17343.8
Maximum	528666
Range	528666
Interquartile range (IQR)	3882.25

Descriptive statistics

Standard deviation	17777.46578
Coefficient of variation (CV)	3.408581541
Kurtosis	167.1614296
Mean	5215.502567
Median Absolute Deviation (MAD)	1500
Skewness	10.64072733
Sum	156465077
Variance	316038289.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	7173	23.9%
1000	1299	4.3%
2000	1295	4.3%
3000	914	3.0%
5000	808	2.7%
1500	439	1.5%
4000	411	1.4%
10000	356	1.2%
500	247	0.8%
6000	220	0.7%
Other values (6929)	16838	56.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	7173	23.9%
1	20	0.1%
2	9	< 0.1%
3	14	< 0.1%
4	12	< 0.1%
5	7	< 0.1%
6	6	< 0.1%
7	5	< 0.1%
8	6	< 0.1%
9	7	< 0.1%

Value	Count	Frequency (%)
528666	1	< 0.1%
527143	1	< 0.1%
443001	1	< 0.1%
422000	1	< 0.1%
403500	1	< 0.1%
377000	1	< 0.1%
372495	1	< 0.1%
351282	1	< 0.1%
345293	1	< 0.1%
308000	1	< 0.1%

default_payment_next_month
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	29.5 KiB

0	23364
1	6636

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring characters

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

pay_1_-1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	24314
1	5686

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	24314	81.0%
1	5686	19.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24314	81.0%
1	5686	19.0%

Most occurring characters

Value	Count	Frequency (%)
0	24314	81.0%
1	5686	19.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24314	81.0%
1	5686	19.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24314	81.0%
1	5686	19.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24314	81.0%
1	5686	19.0%

pay_1_0
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	15263
1	14737

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	15263	50.9%
1	14737	49.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	15263	50.9%
1	14737	49.1%

Most occurring characters

Value	Count	Frequency (%)
0	15263	50.9%
1	14737	49.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	15263	50.9%
1	14737	49.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	15263	50.9%
1	14737	49.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	15263	50.9%
1	14737	49.1%

pay_1_1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	26312
1	3688

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	26312	87.7%
1	3688	12.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	26312	87.7%
1	3688	12.3%

Most occurring characters

Value	Count	Frequency (%)
0	26312	87.7%
1	3688	12.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	26312	87.7%
1	3688	12.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	26312	87.7%
1	3688	12.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	26312	87.7%
1	3688	12.3%

pay_1_2
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	27333
1	2667

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	27333	91.1%
1	2667	8.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	27333	91.1%
1	2667	8.9%

Most occurring characters

Value	Count	Frequency (%)
0	27333	91.1%
1	2667	8.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	27333	91.1%
1	2667	8.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	27333	91.1%
1	2667	8.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	27333	91.1%
1	2667	8.9%

pay_1_3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29678
1	322

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29678	98.9%
1	322	1.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29678	98.9%
1	322	1.1%

Most occurring characters

Value	Count	Frequency (%)
0	29678	98.9%
1	322	1.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29678	98.9%
1	322	1.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29678	98.9%
1	322	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29678	98.9%
1	322	1.1%

pay_1_4
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29924
1	76

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

pay_1_5
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29974
1	26

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29974	99.9%
1	26	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29974	99.9%
1	26	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29974	99.9%
1	26	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29974	99.9%
1	26	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29974	99.9%
1	26	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29974	99.9%
1	26	0.1%

pay_1_6
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29989
1	11

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29989	> 99.9%
1	11	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29989	> 99.9%
1	11	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29989	> 99.9%
1	11	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29989	> 99.9%
1	11	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29989	> 99.9%
1	11	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29989	> 99.9%
1	11	< 0.1%

pay_1_7
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29991
1	9

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29991	> 99.9%
1	9	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29991	> 99.9%
1	9	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29991	> 99.9%
1	9	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29991	> 99.9%
1	9	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29991	> 99.9%
1	9	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29991	> 99.9%
1	9	< 0.1%

pay_1_8
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29981
1	19

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

pay_2_-1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	23950
1	6050

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	23950	79.8%
1	6050	20.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	23950	79.8%
1	6050	20.2%

Most occurring characters

Value	Count	Frequency (%)
0	23950	79.8%
1	6050	20.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	23950	79.8%
1	6050	20.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	23950	79.8%
1	6050	20.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	23950	79.8%
1	6050	20.2%

pay_2_0
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	15730
0	14270

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	15730	52.4%
0	14270	47.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	15730	52.4%
0	14270	47.6%

Most occurring characters

Value	Count	Frequency (%)
1	15730	52.4%
0	14270	47.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	15730	52.4%
0	14270	47.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	15730	52.4%
0	14270	47.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	15730	52.4%
0	14270	47.6%

pay_2_1
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29972
1	28

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29972	99.9%
1	28	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29972	99.9%
1	28	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29972	99.9%
1	28	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29972	99.9%
1	28	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29972	99.9%
1	28	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29972	99.9%
1	28	0.1%

pay_2_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	26073
1	3927

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	26073	86.9%
1	3927	13.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	26073	86.9%
1	3927	13.1%

Most occurring characters

Value	Count	Frequency (%)
0	26073	86.9%
1	3927	13.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	26073	86.9%
1	3927	13.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	26073	86.9%
1	3927	13.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	26073	86.9%
1	3927	13.1%

pay_2_3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29674
1	326

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29674	98.9%
1	326	1.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29674	98.9%
1	326	1.1%

Most occurring characters

Value	Count	Frequency (%)
0	29674	98.9%
1	326	1.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29674	98.9%
1	326	1.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29674	98.9%
1	326	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29674	98.9%
1	326	1.1%

pay_2_4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29901
1	99

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29901	99.7%
1	99	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29901	99.7%
1	99	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	29901	99.7%
1	99	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29901	99.7%
1	99	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29901	99.7%
1	99	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29901	99.7%
1	99	0.3%

pay_2_5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29975
1	25

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29975	99.9%
1	25	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29975	99.9%
1	25	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29975	99.9%
1	25	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29975	99.9%
1	25	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29975	99.9%
1	25	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29975	99.9%
1	25	0.1%

pay_2_6
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29988
1	12

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29988	> 99.9%
1	12	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29988	> 99.9%
1	12	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29988	> 99.9%
1	12	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29988	> 99.9%
1	12	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29988	> 99.9%
1	12	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29988	> 99.9%
1	12	< 0.1%

pay_2_7
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29980
1	20

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29980	99.9%
1	20	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29980	99.9%
1	20	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29980	99.9%
1	20	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29980	99.9%
1	20	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29980	99.9%
1	20	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29980	99.9%
1	20	0.1%

pay_2_8
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29999
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

pay_3_-1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	24062
1	5938

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	24062	80.2%
1	5938	19.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24062	80.2%
1	5938	19.8%

Most occurring characters

Value	Count	Frequency (%)
0	24062	80.2%
1	5938	19.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24062	80.2%
1	5938	19.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24062	80.2%
1	5938	19.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24062	80.2%
1	5938	19.8%

pay_3_0
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	15764
0	14236

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	15764	52.5%
0	14236	47.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	15764	52.5%
0	14236	47.5%

Most occurring characters

Value	Count	Frequency (%)
1	15764	52.5%
0	14236	47.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	15764	52.5%
0	14236	47.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	15764	52.5%
0	14236	47.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	15764	52.5%
0	14236	47.5%

pay_3_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29996
1	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

pay_3_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	26181
1	3819

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	26181	87.3%
1	3819	12.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	26181	87.3%
1	3819	12.7%

Most occurring characters

Value	Count	Frequency (%)
0	26181	87.3%
1	3819	12.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	26181	87.3%
1	3819	12.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	26181	87.3%
1	3819	12.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	26181	87.3%
1	3819	12.7%

pay_3_3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29760
1	240

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29760	99.2%
1	240	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29760	99.2%
1	240	0.8%

Most occurring characters

Value	Count	Frequency (%)
0	29760	99.2%
1	240	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29760	99.2%
1	240	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29760	99.2%
1	240	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29760	99.2%
1	240	0.8%

pay_3_4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29924
1	76

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29924	99.7%
1	76	0.3%

pay_3_5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29979
1	21

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29979	99.9%
1	21	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29979	99.9%
1	21	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29979	99.9%
1	21	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29979	99.9%
1	21	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29979	99.9%
1	21	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29979	99.9%
1	21	0.1%

pay_3_6
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29977
1	23

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29977	99.9%
1	23	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29977	99.9%
1	23	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29977	99.9%
1	23	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29977	99.9%
1	23	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29977	99.9%
1	23	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29977	99.9%
1	23	0.1%

pay_3_7
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29973
1	27

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29973	99.9%
1	27	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29973	99.9%
1	27	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29973	99.9%
1	27	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29973	99.9%
1	27	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29973	99.9%
1	27	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29973	99.9%
1	27	0.1%

pay_3_8
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29997
1	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29997	> 99.9%
1	3	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29997	> 99.9%
1	3	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29997	> 99.9%
1	3	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29997	> 99.9%
1	3	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29997	> 99.9%
1	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29997	> 99.9%
1	3	< 0.1%

pay_4_-1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	24313
1	5687

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	24313	81.0%
1	5687	19.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24313	81.0%
1	5687	19.0%

Most occurring characters

Value	Count	Frequency (%)
0	24313	81.0%
1	5687	19.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24313	81.0%
1	5687	19.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24313	81.0%
1	5687	19.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24313	81.0%
1	5687	19.0%

pay_4_0
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	16455
0	13545

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	16455	54.9%
0	13545	45.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	16455	54.9%
0	13545	45.1%

Most occurring characters

Value	Count	Frequency (%)
1	16455	54.9%
0	13545	45.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	16455	54.9%
0	13545	45.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	16455	54.9%
0	13545	45.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	16455	54.9%
0	13545	45.1%

pay_4_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29998
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

pay_4_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	26841
1	3159

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	26841	89.5%
1	3159	10.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	26841	89.5%
1	3159	10.5%

Most occurring characters

Value	Count	Frequency (%)
0	26841	89.5%
1	3159	10.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	26841	89.5%
1	3159	10.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	26841	89.5%
1	3159	10.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	26841	89.5%
1	3159	10.5%

pay_4_3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29820
1	180

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29820	99.4%
1	180	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29820	99.4%
1	180	0.6%

Most occurring characters

Value	Count	Frequency (%)
0	29820	99.4%
1	180	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29820	99.4%
1	180	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29820	99.4%
1	180	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29820	99.4%
1	180	0.6%

pay_4_4
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29931
1	69

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29931	99.8%
1	69	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29931	99.8%
1	69	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	29931	99.8%
1	69	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29931	99.8%
1	69	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29931	99.8%
1	69	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29931	99.8%
1	69	0.2%

pay_4_5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29965
1	35

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29965	99.9%
1	35	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29965	99.9%
1	35	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29965	99.9%
1	35	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29965	99.9%
1	35	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29965	99.9%
1	35	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29965	99.9%
1	35	0.1%

pay_4_6
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29995
1	5

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29995	> 99.9%
1	5	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29995	> 99.9%
1	5	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29995	> 99.9%
1	5	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29995	> 99.9%
1	5	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29995	> 99.9%
1	5	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29995	> 99.9%
1	5	< 0.1%

pay_4_7
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29942
1	58

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

pay_4_8
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29998
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

pay_5_-1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	24461
1	5539

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	24461	81.5%
1	5539	18.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24461	81.5%
1	5539	18.5%

Most occurring characters

Value	Count	Frequency (%)
0	24461	81.5%
1	5539	18.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24461	81.5%
1	5539	18.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24461	81.5%
1	5539	18.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24461	81.5%
1	5539	18.5%

pay_5_0
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	16947
0	13053

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	16947	56.5%
0	13053	43.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	16947	56.5%
0	13053	43.5%

Most occurring characters

Value	Count	Frequency (%)
1	16947	56.5%
0	13053	43.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	16947	56.5%
0	13053	43.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	16947	56.5%
0	13053	43.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	16947	56.5%
0	13053	43.5%

pay_5_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	27374
1	2626

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	27374	91.2%
1	2626	8.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	27374	91.2%
1	2626	8.8%

Most occurring characters

Value	Count	Frequency (%)
0	27374	91.2%
1	2626	8.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	27374	91.2%
1	2626	8.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	27374	91.2%
1	2626	8.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	27374	91.2%
1	2626	8.8%

pay_5_3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29822
1	178

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29822	99.4%
1	178	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29822	99.4%
1	178	0.6%

Most occurring characters

Value	Count	Frequency (%)
0	29822	99.4%
1	178	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29822	99.4%
1	178	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29822	99.4%
1	178	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29822	99.4%
1	178	0.6%

pay_5_4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29916
1	84

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29916	99.7%
1	84	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29916	99.7%
1	84	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	29916	99.7%
1	84	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29916	99.7%
1	84	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29916	99.7%
1	84	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29916	99.7%
1	84	0.3%

pay_5_5
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29983
1	17

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29983	99.9%
1	17	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29983	99.9%
1	17	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29983	99.9%
1	17	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29983	99.9%
1	17	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29983	99.9%
1	17	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29983	99.9%
1	17	0.1%

pay_5_6
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29996
1	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29996	> 99.9%
1	4	< 0.1%

pay_5_7
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29942
1	58

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29942	99.8%
1	58	0.2%

pay_5_8
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29999
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29999	> 99.9%
1	1	< 0.1%

pay_6_-1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	24260
1	5740

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	24260	80.9%
1	5740	19.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24260	80.9%
1	5740	19.1%

Most occurring characters

Value	Count	Frequency (%)
0	24260	80.9%
1	5740	19.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24260	80.9%
1	5740	19.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24260	80.9%
1	5740	19.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24260	80.9%
1	5740	19.1%

pay_6_0
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	16286
0	13714

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	16286	54.3%
0	13714	45.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	16286	54.3%
0	13714	45.7%

Most occurring characters

Value	Count	Frequency (%)
1	16286	54.3%
0	13714	45.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	16286	54.3%
0	13714	45.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	16286	54.3%
0	13714	45.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	16286	54.3%
0	13714	45.7%

pay_6_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	27234
1	2766

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	27234	90.8%
1	2766	9.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	27234	90.8%
1	2766	9.2%

Most occurring characters

Value	Count	Frequency (%)
0	27234	90.8%
1	2766	9.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	27234	90.8%
1	2766	9.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	27234	90.8%
1	2766	9.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	27234	90.8%
1	2766	9.2%

pay_6_3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29816
1	184

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29816	99.4%
1	184	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29816	99.4%
1	184	0.6%

Most occurring characters

Value	Count	Frequency (%)
0	29816	99.4%
1	184	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29816	99.4%
1	184	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29816	99.4%
1	184	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29816	99.4%
1	184	0.6%

pay_6_4
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29951
1	49

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29951	99.8%
1	49	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29951	99.8%
1	49	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	29951	99.8%
1	49	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29951	99.8%
1	49	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29951	99.8%
1	49	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29951	99.8%
1	49	0.2%

pay_6_5
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29987
1	13

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29987	> 99.9%
1	13	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29987	> 99.9%
1	13	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29987	> 99.9%
1	13	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29987	> 99.9%
1	13	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29987	> 99.9%
1	13	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29987	> 99.9%
1	13	< 0.1%

pay_6_6
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29981
1	19

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29981	99.9%
1	19	0.1%

pay_6_7
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29954
1	46

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29954	99.8%
1	46	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29954	99.8%
1	46	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	29954	99.8%
1	46	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29954	99.8%
1	46	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29954	99.8%
1	46	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29954	99.8%
1	46	0.2%

pay_6_8
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29998
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29998	> 99.9%
1	2	< 0.1%

female
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	18112
0	11888

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	18112	60.4%
0	11888	39.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	18112	60.4%
0	11888	39.6%

Most occurring characters

Value	Count	Frequency (%)
1	18112	60.4%
0	11888	39.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	18112	60.4%
0	11888	39.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	18112	60.4%
0	11888	39.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	18112	60.4%
0	11888	39.6%

education_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	19415
1	10585

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	19415	64.7%
1	10585	35.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	19415	64.7%
1	10585	35.3%

Most occurring characters

Value	Count	Frequency (%)
0	19415	64.7%
1	10585	35.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	19415	64.7%
1	10585	35.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	19415	64.7%
1	10585	35.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	19415	64.7%
1	10585	35.3%

education_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	15970
1	14030

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	15970	53.2%
1	14030	46.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	15970	53.2%
1	14030	46.8%

Most occurring characters

Value	Count	Frequency (%)
0	15970	53.2%
1	14030	46.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	15970	53.2%
1	14030	46.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	15970	53.2%
1	14030	46.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	15970	53.2%
1	14030	46.8%

education_3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	25083
1	4917

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	25083	83.6%
1	4917	16.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	25083	83.6%
1	4917	16.4%

Most occurring characters

Value	Count	Frequency (%)
0	25083	83.6%
1	4917	16.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	25083	83.6%
1	4917	16.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	25083	83.6%
1	4917	16.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	25083	83.6%
1	4917	16.4%

education_4
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29546
1	454

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29546	98.5%
1	454	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29546	98.5%
1	454	1.5%

Most occurring characters

Value	Count	Frequency (%)
0	29546	98.5%
1	454	1.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29546	98.5%
1	454	1.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29546	98.5%
1	454	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29546	98.5%
1	454	1.5%

education_5
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	30000

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	30000	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	30000	100.0%

education_6
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	30000

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	30000	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	30000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	30000	100.0%

marriage_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	16341
1	13659

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	16341	54.5%
1	13659	45.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	16341	54.5%
1	13659	45.5%

Most occurring characters

Value	Count	Frequency (%)
0	16341	54.5%
1	13659	45.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	16341	54.5%
1	13659	45.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	16341	54.5%
1	13659	45.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	16341	54.5%
1	13659	45.5%

marriage_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

1	15964
0	14036

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	15964	53.2%
0	14036	46.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	15964	53.2%
0	14036	46.8%

Most occurring characters

Value	Count	Frequency (%)
1	15964	53.2%
0	14036	46.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	15964	53.2%
0	14036	46.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	15964	53.2%
0	14036	46.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	15964	53.2%
0	14036	46.8%

marriage_3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

0	29623
1	377

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	29623	98.7%
1	377	1.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	29623	98.7%
1	377	1.3%

Most occurring characters

Value	Count	Frequency (%)
0	29623	98.7%
1	377	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	29623	98.7%
1	377	1.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	29623	98.7%
1	377	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	29623	98.7%
1	377	1.3%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Matrix

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	id	limit_bal	age	bill_amt1	bill_amt2	bill_amt3	bill_amt4	bill_amt5	bill_amt6	pay_amt1	pay_amt2	pay_amt3	pay_amt4	pay_amt5	pay_amt6	default_payment_next_month	pay_1_-1	pay_1_0	pay_1_2	pay_2_-1	pay_2_0	pay_2_2	pay_3_-1	pay_3_0	pay_3_2	pay_4_-1	pay_4_0	pay_5_-1	pay_5_0	pay_6_-1	pay_6_0	pay_6_2	female	education_1	education_2	education_3	marriage_1	marriage_2
0	1	20000.0	24	3913.0	3102.0	689.0	0.0	0.0	0.0	0.0	689.0	0.0	0.0	0.0	0.0	1	0	0	1	0	0	1	1	0	0	1	0	0	0	0	0	0	1	0	1	0	1	0
1	2	120000.0	26	2682.0	1725.0	2682.0	3272.0	3455.0	3261.0	0.0	1000.0	1000.0	1000.0	0.0	2000.0	1	1	0	0	0	0	1	0	1	0	0	1	0	1	0	0	1	1	0	1	0	0	1
2	3	90000.0	34	29239.0	14027.0	13559.0	14331.0	14948.0	15549.0	1518.0	1500.0	1000.0	1000.0	1000.0	5000.0	0	0	1	0	0	1	0	0	1	0	0	1	0	1	0	1	0	1	0	1	0	0	1
3	4	50000.0	37	46990.0	48233.0	49291.0	28314.0	28959.0	29547.0	2000.0	2019.0	1200.0	1100.0	1069.0	1000.0	0	0	1	0	0	1	0	0	1	0	0	1	0	1	0	1	0	1	0	1	0	1	0
4	5	50000.0	57	8617.0	5670.0	35835.0	20940.0	19146.0	19131.0	2000.0	36681.0	10000.0	9000.0	689.0	679.0	0	1	0	0	0	1	0	1	0	0	0	1	0	1	0	1	0	0	0	1	0	1	0
5	6	50000.0	37	64400.0	57069.0	57608.0	19394.0	19619.0	20024.0	2500.0	1815.0	657.0	1000.0	1000.0	800.0	0	0	1	0	0	1	0	0	1	0	0	1	0	1	0	1	0	0	1	0	0	0	1
6	7	500000.0	29	367965.0	412023.0	445007.0	542653.0	483003.0	473944.0	55000.0	40000.0	38000.0	20239.0	13750.0	13770.0	0	0	1	0	0	1	0	0	1	0	0	1	0	1	0	1	0	0	1	0	0	0	1
7	8	100000.0	23	11876.0	380.0	601.0	221.0	-159.0	567.0	380.0	601.0	0.0	581.0	1687.0	1542.0	0	0	1	0	1	0	0	1	0	0	0	1	0	1	1	0	0	1	0	1	0	0	1
8	9	140000.0	28	11285.0	14096.0	12108.0	12211.0	11793.0	3719.0	3329.0	0.0	432.0	1000.0	1000.0	1000.0	0	0	1	0	0	1	0	0	0	1	0	1	0	1	0	1	0	1	0	0	1	1	0
9	10	20000.0	35	0.0	0.0	0.0	0.0	13007.0	13912.0	0.0	0.0	0.0	13007.0	1122.0	0.0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0	1

Last rows

	id	limit_bal	age	bill_amt1	bill_amt2	bill_amt3	bill_amt4	bill_amt5	bill_amt6	pay_amt1	pay_amt2	pay_amt3	pay_amt4	pay_amt5	pay_amt6	default_payment_next_month	pay_1_-1	pay_1_0	pay_1_1	pay_1_2	pay_1_3	pay_1_4	pay_2_-1	pay_2_0	pay_2_2	pay_2_3	pay_3_-1	pay_3_0	pay_3_2	pay_4_-1	pay_4_0	pay_4_2	pay_5_0	pay_5_2	pay_6_-1	pay_6_0	pay_6_2	education_1	education_2	education_3	marriage_1	marriage_2
29990	29991	140000.0	41	138325.0	137142.0	139110.0	138262.0	49675.0	46121.0	6000.0	7000.0	4228.0	1505.0	2000.0	2000.0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0	0	1	0	0	1	0	1	0
29991	29992	210000.0	34	2500.0	2500.0	2500.0	2500.0	2500.0	2500.0	0.0	0.0	0.0	0.0	0.0	0.0	1	0	0	0	0	1	0	0	0	1	0	0	0	1	0	0	1	0	1	0	0	1	0	1	0	1	0
29992	29993	10000.0	43	8802.0	10400.0	0.0	0.0	0.0	0.0	2000.0	0.0	0.0	0.0	0.0	0.0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0
29993	29994	100000.0	38	3042.0	1427.0	102996.0	70626.0	69473.0	55004.0	2000.0	111784.0	4000.0	3000.0	2000.0	2000.0	0	0	1	0	0	0	0	1	0	0	0	1	0	0	0	1	0	1	0	0	1	0	1	0	0	0	1
29994	29995	80000.0	34	72557.0	77708.0	79384.0	77519.0	82607.0	81158.0	7000.0	3500.0	0.0	7000.0	0.0	4000.0	1	0	0	0	1	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0	0	1	0	1	0	0	1
29995	29996	220000.0	39	188948.0	192815.0	208365.0	88004.0	31237.0	15980.0	8500.0	20000.0	5003.0	3047.0	5000.0	1000.0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0	0	1	0	0	0	1	1	0
29996	29997	150000.0	43	1683.0	1828.0	3502.0	8979.0	5190.0	0.0	1837.0	3526.0	8998.0	129.0	0.0	0.0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0	1	0	0	1	0	0	0	1	0	1
29997	29998	30000.0	37	3565.0	3356.0	2758.0	20878.0	20582.0	19357.0	0.0	0.0	22000.0	4200.0	2000.0	3100.0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0	0	1	0	0	1	0	0	1	0	0	1
29998	29999	80000.0	41	-1645.0	78379.0	76304.0	52774.0	11855.0	48944.0	85900.0	3409.0	1178.0	1926.0	52964.0	1804.0	1	0	0	1	0	0	0	1	0	0	0	0	1	0	0	1	0	1	0	1	0	0	0	0	1	1	0
29999	30000	50000.0	46	47929.0	48905.0	49764.0	36535.0	32428.0	15313.0	2078.0	1800.0	1430.0	1000.0	1000.0	1000.0	1	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0	0	1	0	0	1	0	1	0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII